This report contains a descriptive analysis of fisheries in Trujillo, based on the sampled, time-series database of fish landings collected by CORAL and its partners.
# ==== Data preparation ====
# Preparing columns
dat <- dat |>
# Using the cleaned common names as default
mutate(nc_og = nombre_comun) |>
mutate(nombre_comun = str_to_title(nombre_comun_cln)) |>
# Adding "sp" to columns where the genus is present but no species is present
mutate(species = if_else((is.na(species) & !is.na(genus)), 'sp', species)) |>
tidyr::unite(nombre_cientifico, genus, species, sep=' ', remove=F, na.rm=T) |>
# Factorizing relevant columns
mutate(comunidad = as.factor(comunidad)) |>
mutate(zona_pesca = as.factor(zona_pesca)) |>
# Getting year, month, and year-month columns
mutate(year = year(fecha), month=month(fecha), .after='fecha') |>
mutate(ym = paste(year, str_pad(month, 2, 'left', '0'), sep='-'), .after=month) |>
mutate(month = month.abb[month]) |>
# Factorizing year and month column
mutate(year = as.factor(year)) |>
mutate(month = factor(month, levels=month.abb)) |>
# Converting weight to kg
mutate(peso = peso/1000)
# Removing rows where no date is given
dat <- dat |> filter(!is.na(fecha))
# Removing outliers (detected based on IQR ranges specific to each
# genus/family) - based on weight
dat <- dat |>
# A helper grouping variable that uses the family name if the scientific name
# is not available
mutate(taxa = if_else(is.na(nombre_cientifico), family, nombre_cientifico)) |>
group_by(taxa) |>
# Naming outliers for each taxa group
mutate(isoutlier = ifelse(all(is.na(peso)), 'No', anomalize::iqr(peso))) |>
ungroup()
# Separating those that are outliers for manual inspection - they don't look
# unreasonable, so not removing anything
outliers <- dat |> filter(isoutlier == "Yes")
# Cleaing outliers
dat <- dat |>
# Removing unreasonable weight rows
filter(peso < 40) |>
# filter(isoutlier == "No") |>
# Removing outlier related fields
select(-isoutlier, -taxa)
## [1] "Diversided de especias capturadas por comunidad:"
## Capiro Jerico Castilla Cristales Rio Negro San Martin
## 2.532314 2.404296 2.395181 2.023227 2.263530
## Silin
## 1.064363
## [1] "Diversidad de especias capturadas por tipo de arte:"
## Chinchorro Cuerda Cuerda y trasmallo Nasa
## 0.8723983 2.3582201 0.9649629 2.0524470
## Trasmallo
## 2.5229556
## [1] "Diversidad de tipos de artes por comunidad:"
## Capiro Jerico Castilla Cristales Rio Negro San Martin
## 0.2605994 0.4509718 0.5801219 0.0000000 0.6554818
## Silin
## 0.0000000
Maturity data were only gathered for a small subset of the total sampling effort. The observations which contain maturity data have the following characteristics:
## [1] "Total number of observations with maturity data: 0"
## [1] "Date range: Inf" "Date range: -Inf"
## [1] "Number of maturity observations by species:"
## < table of extent 0 >